Lou Tommy. / "Architecture Department, Chinese University of Hong Kong, Master of Architecture Programme 2007-2008, design report."

This paper summarizes a panel discussion at the 15th International Conference on Business Process Management. The panel discussed to what extent the emergence of recent technologies including machine learning, robotic process automation, and blockchain will reduce the human factor in business process management. The panel discussion took place on 14 September, 2017, at the Universitat Politècnica de Catalunya in Barcelona, Spain. Jan Mendling served as a chair; Gero Decker, Richard Hull, Hajo Reijers, and Ingo Weber participated as panelists. The discussions emphasized the impact of emerging technologies at the task level and the coordination level. The major challenges that the panel identified relate to employment, technology acceptance, ethics, customer experience, job design, social integration, and regulation.

In driving, multiple variables in automated systems such as adaptive cruise control (ACC) and active steering, and in the environment dynamically change and interact. This complexity makes it difficult for operators to track the activities and responses of automation. The inability of operators to monitor and understand automation's behavior contributes to inappropriate reliance, i.e. when an operator uses automation that performs poorly or fails to use automation that is superior to manual control. The decision to use or not use automation is one of the most important an operator can make, particularly in time-critical or emergency situations, therefore it is essential that an operator is calibrated in their automation use. An operator's decision to rely on automation depends on trust. System feedback provided to the operator is one means to calibrate trust in automation in that the type of feedback may differentially affect trust. The goal of this research is to help operators manage imperfect automation in real-time and to promote calibrated trust and reliance. A continuous information display that provides information on system behavior relative to its operating context is one means to promote such calibration. Three specific aims are pursued to test the central hypothesis of this dissertation that continuous feedback on the state and behavior of the automation informs operators of the evolving relationship between system performance and operating limits, therefore promoting accurate mental models and calibrated trust. The first aim applies a quantitative model to define the effect of understanding on driver-ACC interaction failures and to predict driver response to feedback. The second aim presents a systematic approach to define the feedback needed to support appropriate reliance in a demanding multi-task domain such as driving. The third aim assesses the costs and benefits of presenting drivers with continuous visual and auditory feedback. Together these aims indicate that continuous feedback on automation's behavior is a viable means to promote calibrated trust and reliance. The contribution of this dissertation is in providing purpose, process, and performance information to operators through a continuous, concurrent information display that indicates how the given situation interacts with the characteristics of the automation to affect its capability.

Automated storage and Retrieval (AS/R) systems have had a significant impact on storage and retrieval of finished goods, work-in-process, and raw materials and supplies. A microcomputer-based simulation model was developed to evaluate different unit load AS/R systems serving multiple input sources and output destinations. The simulation results were statistically analyzed on different performance measures including throughput, mean waiting times maximum waiting times and rejects. The results showed that for single-dock, square-in-time layouts, the class based arrangement produced significantly higher throughput for all scheduling policies. Among the scheduling policies, the relief nearest neighbor produced consistently higher throughput. Comparing square-in-time versus non-square-in-time layouts, the square-in-time layout performance was better; the performance deteriorated as deviations from square-in-time increased. For the two dual-dock layouts, at lower arrival rates the dedicated layout produced higher throughput; there was no significant difference between the two layouts at higher arrival rates. / Graduation date: 1992

A large body of research has identified that one of the major factors influencing decisions about automation use is operator's trust. Studies have shown that operator trust can be affected by individual differences in expectancy. The purpose of this study was to investigate whether operators with an expectancy that automation is trustworthy are better at calibrating their trust to changes in the capabilities of the automation. We also investigated why this individual difference affects calibration. In a baggage screening task 176 participants searched for weapons in 200 x-ray images of luggage. Participants were assisted by an automated decision aid exhibiting different levels of reliability. Measures of expectancy that automation is trustworthy were used in conjunction with subjective measures of trust and of perceived reliability to identify individual differences in trust calibration. We found that operators with high expectancy that automation is trustworthy were more sensitive to changes (both increases and decreases) in automation reliability, and that this difference was caused by attributing errors to the situation rather than the automation.

Det finns flera fördelar med robotiserad bågsvetsning jämfört med manuell bågsvetsning. När det gäller produktivitet och repeterbarhet är robot överlägsen människa, vilket gör att produkterna håller jämnare kvalitet. I slutet av 80-talet började offline-programmering att tillämpas. Att programmera en robot offline innebär att utföra programmeringen med dator utan direkt tillgång till roboten. Genom simulering visualiseras ett robotprogram i en grafisk modell av den fysiska robotcellen utan att den fysiska roboten behöver tas ur produktion. För att systemet för offline-programmering (OLP) ska vara effektivt, måste dess modellers kinematik överensstämma med dess fysiska motsvarigheter. En virtuell modell av en cell skiljer sig dock alltid något från verkligheten. Därför krävs kalibrering När simuleringsprogrammet är färdigt och kalibreringen är utförd, ska programmet översättas till ett för roboten specifikt programspråk. Detta görs genom en så kallad translator. Denna rapport har skrivits på uppdrag av Delfoi. Delfoi har i flera år använt sig av DELMIA IGRIP för offline-programmering av bågsvetsningsrobotar. DELMIA har nu gett ut en ny generation program i den gemensamma plattformen V5. Plattformen innehåller bland annat DELMIA V5 Robotics och CATIA V5. Området för bågsvetsning har varit relativt outforskat. Därför vill företaget undersöka hur långt V5 Robotics har utvecklats inom detta område. Syftet är att undersöka om utvecklingen av V5 Robotics kommit tillräckligt långt för att kunna säljas till kund för offline-programmering av bågsvetsning. Arbetet påbörjades genom att kartlägga den arbetsmetodik som Delfoi använder sig av vid bågsvetsning i IGRIP. Detta har skett i programvaran UltraArc, som innehåller IGRIP’s applikation för bågsvetsning. Dessutom gjordes en kartläggning av användandet av AMP, Arc weld Macro Programming, vid offline-programmering av bågsvetsning. Nästa del var att ta fram en metodik för bågsvetsning i V5 Robotics. De båda programmen och dess metodik har sedan jämförts, för att ta reda på om V5 Robotics är tillräckligt utvecklat för att migrera från IGRIP till V5 Robotics. Demonstrationer av arbetssättet i V5 Robotics har genomförts på Delfoi samt hos en av Delfois kunder, BT Industries i Mjölby. Författarnas slutsats är att V5 Robotics är redo att användas för OLP av bågsvetsning. För de företag som använder sig av CATIA V5 finns det stora fördelar med att starta migrationen från IGRIP till V5 Robotics. Metodiken mellan de båda mjukvarorna har stora likheter, men vissa delar har utvecklats till det bättre i V5 Robotics. Dock kan den nya programvaran behöva testas i verkliga projekt för att säkerställa att hela programmeringsprocessen fungerar tillfredsställande innan bytet genomförs. / There are several advantages in robotic arc welding, compared to manual arc welding. When it comes to productivity and repeatability, robot is superior to man, which generates more even quality in products. In the end of the 1980’s, offline programming was put into practice. To program a robot offline means to perform the programming on a computer with no direct access to the robot. Through simulation, the robot program is visualized as a graphic model of the actual workcell, without having to take the actual robot out of production. For the offline programming system (OLP) to be efficient, the kinematics of the models need to correspond to its physical counterpart. A virtual model is always slightly different from the reality. That is why calibration is necessary. When the simulation program is complete and the calibration is done, the program needs to be translated to the language of the target robot. This is done through a post processor. This thesis was written as an assignment from the company Delfoi. Delfoi has been using DELMIA IGRIP for offline programming of robotic arc welding for several years. DELMIA now has released a new generation of programs in the common platform V5. The platform includes for example DELMIA V5 Robotics and CATIA V5. The area of arc welding has been relatively unexplored. That is why the company wants to investigate how far V5 Robotics has developed in this area. The purpose is to investigate if the development of V5 Robotics has come far enough for V5 Robotics to be taken to customers for OLP of arc welding. The work was begun by surveying the methodology used by Delfoi in arc welding in IGRIP. This has been done in the software UltraArc, which consists of the arc welding application from IGRIP. There was also a surveillance of the application of AMP, Arc weld Macro Programming, in offline programming of arc welding. The next step was to evolve a methodology for arc welding in V5 Robotics. The two softwares and their methodologies were then compared to find out whether or not V5 is enough developed for migration from IGRIP to V5 Robotics. Demonstrations of the method of working in V5 Robotics were held on Delfoi and on BT Industries in Mjölby, which is one of Deloi’s clients. The conclusion of the writers is that V5 Robotics is ready to be used in OLP of arc welding. For companies using CATIA V5, there are great advantages in migrating from IGRIP to V5 Robotics. The methodoldgies of the softwares show great similarities, but some parts have been developed to the better in V5 Robotics. Though, the new software needs to be tested in real projects to assure that the entire process of programming functions satisfying before the change is completed.

This work develops optimal assembly sequences for modular building blocks. The underlying concept is that an automated device could take a virtual shape such as a CAD file, and automatically decide how to physically build the shape using simple, identical building blocks. This entails deciding where to place blocks inside the shape and generating an efficient assembly sequence that a robot could use to build the shape. The blocks are defined in a general, parameterized manner such that the model can be easily modified in the future. The primary focus of this work is the development of methods for generating assembly sequences in a time-feasible manner that ensure static stability at each step of the assembly. Most existing research focuses on complete enumeration of every possible assembly sequence and evaluation of many possible sequences. This, however, is not practical for systems with a large number of parts for two reasons: (1) the number of possible assembly sequences is exponential in the number of parts, and (2) each static stability test is very time-consuming. The approach proposed here is to develop a multi-hierarchical rule-based approach to assembly sequences. This is accomplished by formalizing and justifying both high-level and mid-level assembly rules based on static considerations. Application of these rules helps develop assembly sequences rapidly. The assembly sequence is developed in a time-feasible manner according to the geometry of the structure, rather than evaluating statics along the way. This work only evaluates the static stability of each step of the assembly once. The behavior of the various rules is observed both numerically and through theory, and guidelines are developed to suggest which rules to apply. A secondary focus of this work is to introduce methods by which the inside of the structure can be optimized. This structure optimization research is implemented by genetic algorithms that solve the multi-objective optimization problem in two dimensions, and can be extended to three dimensions.

This work follows the design, prototyping and implementation of an automatic part loading and unloading system for use in thread rolling of aerospace fasteners. The thread rolling automation system is designed to function as part of a multi-process workcell, which emphasizes adaptability and ease of implementation. Design of the thread rolling automation facilitates the development of a universal gripping system, which is designed to grasp a large variety of fastener styles and sizes with a minimum of tooling changeover. A novel grasping model is developed to predict the error tolerance of the proposed gripping system design, which is validated experimentally. The proposed gripper and automation system are prototyped and tested, and shown to perform reliably with a wide range of fastener types.

Automation provides the opportunity for many tasks to be done more effectively and with greater safety. However, these benefits are unlikely to be attained if an automated system is designed without the human user in mind. Many characteristics of the human and automation, such as trust and reliability, have been rigorously examined in the literature in an attempt to move towards a comprehensive understanding of the interaction between human and machine. However, workload has primarily been examined solely as an outcome variable, rather than as a predictor of compliance, reliance, and performance. This study was designed to gain a deeper understanding of whether workload experienced by human operators influences compliance with and reliance on an automated warehouse management system, as well to assess whether age-related differences exist in this interaction. As workload increased, performance on the Receiving Packages task decreased among younger and older adults. Although younger adults also experienced a negative effect of workload on Dispatching Trucks performance, older adults did not demonstrate a significant effect. The compliance data showed that as workload increased, younger adults complied with the automation to a greater degree, and this was true regardless of whether the automation was correct or incorrect. Older adults did not demonstrate a reliable effect of workload on compliance behavior. Regarding reliance behavior, as workload increased, reliance on the automation increased, but this effect was only observed among older adults. Again, this was true regardless of whether the automation as correct or incorrect. The finding that individuals may be more likely to comply with or rely on faulty automation if they are in high workload state compared to a low workload state suggests that an operator's ability to detect automation errors may be compromised in high workload situations. Overall, younger adults outperformed older adults on the task. Additionally, older adults complied with the system more than younger adults when the system erred, which may have contributed to their poorer performance. When older adults verified the instructions given by the automation, they spent longer doing so than younger adults, suggesting that older adults may experience a greater cost of verification. Further, older adults reported higher workload and greater trust in the system than younger adults, but both age groups perceived the reliability of the system quite accurately. Understanding how workload and age influence automation use has implications for the way in which individuals are trained to interact with complex systems, as well as the situations in which automation implementation is determined to be appropriate.

Multiple-task environments are pervasive in a variety of workplaces; many jobs require several concurrent, time-sensitive tasks be done in one task space. One concern in these multiple-task environments is attention allocation: To perform well, the operator must be able to know when and where to look. Otherwise, he or she will not be aware of the status of each task or be able to complete them. To aid these jobs, automation has been developed to support attention allocation: Auditory and visual alerts draw attention to where the system determines it is needed. However, imperfect automation may complicate the aid by introducing misses and false alarms to which the operator must also attend. Researchers studying these environments and automation's purview within them have focused on a variety of different topics. Some examples include: different types of automation (alerts, decision aid systems, etc.), levels of reliability (0-100% reliable), what automation supports (attention allocation to situation awareness to performance), and how automation affects multiple task environments (two tasks to many). Because attention had not been directly studied in relation to imperfect automation reliability in multiple-task environments, I decided to analyze the effects of different levels of automation reliability on visual attention allocation and how removal of that automation changed those effects. To study this, I helped to develop the Simultaneous Task Environment Platform (STEP), a program to study and test participants' behavior in multiple-task environments. The STEP program enabled me to vary the frequency and criticality (number of points gained/lost) of the different tasks to disambiguate how automation was affecting the participants. In the study, participants were trained on all four tasks of the STEP system, had the automation explained to them, and then were asked to gain as many points a trial as possible. There were three between-subject conditions; a system where ~70% of the automated alerts were reliable, one where ~90% of the alerts were reliable, and one where the participants received no automated aid at all. The automation was designed to support visual attention allocation. The participants interacted with the system and automation for twenty-four trials, divided into six blocks over two days, at which point they transferred to a system with no automation at all. To better understand exactly how the participants interacted with the system, I measured the number of times they accessed each task (attention allocation, as well as a measure of workload) and the number of points they scored (task performance). Mixed ANOVAs for these two measures, as well as a derived measure of efficiency (points scored per window opened), were conducted crossing automation condition with Block (to measure how the participants changed with experience) and task (to measure how certain tasks' attributes affected the way they were acted upon). Overall, the automation provided a benefit in terms of reduced workload and improved task performance. Participants in the automated conditions opened fewer windows and performed better. This also meant higher efficiency for those conditions. Experience affected conditions differentially. Those in the no automation condition increased their score but also the number of windows opened, causing their efficiency to stay the same. The 70% reliable condition was similar, with a minor point increase and no significant window decrease, resulting in no significant efficiency gain. The 90% reliable condition gained little score boost, but opened fewer windows by the end of the experiment, becoming more efficient. The frequency and criticality of tasks affected both the windows opened and the points scored across conditions, as participants in the two automated conditions opened fewer windows and scored relatively more points on those tasks worth many points that did not appear often. This increased their efficiency on those tasks, but also caused them to suffer greater when the automation was taken away. In the transfer trials, those participants in the automated conditions experienced both a workload increase and a performance decrease. These were centered on the two high-criticality/low-frequency tasks, as the other two tasks showed only small or no change between normal and transfer trials. These results show that automation at different levels of reliability affects the behavior of the operator of that system differentially based on the attributes of the tasks the operator must oversee. Tasks that happen often and are only important when aggregated over many are not aided by automation as much as those tasks that happen rarely and are critical every time they appear. When automation fails, however, those same tasks that are aided the most suffer the most, whereas those that do not get much aid do not suffer as much. Designers of automated systems should consider the type of tasks to be automated and their attributes, as well as the effects of increasing or decreasing the reliability of the automation when designing automation to provide support to system operators.